Matrix-assisted laser desorption ionization mass spectrometry for identification of shrimp

Matrix-assisted laser desorption ionization (MALDI) time of flight mass spectrometry was used to identify shrimp at the species level using commercial mass spectral fingerprint matching software (Bruker Biotyper). In the first step, a mass spectrum reference database was constructed from the analysis of six commercially important shrimp species: Litopenaeus setiferus, Farfantepenaeus aztecus, Sicyonia brevirostris, Pleoticus robustus, Pandalopsis dispar and Pandalus platyceros. This step required a desalting procedure for optimum performance. In the second step, the reference database was tested using 74 unknown shrimp samples from these six species. Correct identification was achieved for 72 of 74 samples (97%): 72 samples were identified at the species level and 2 samples were identified at the genus level using the manufacturer's log score specifications. The MALDI fingerprinting method for the identification of shrimp species was found to be reproducible and accurate with rapid analysis.     

Hydrophilic interaction liquid chromatography coupled with MS/MS to detect and quantify dicarboxyethyl glutathione,a metabolic biomarker of the fumarate hydratase deficient cancer cell

The identification of a glutathione (GSH) fumarate conjugate, dicarboxyethyl glutathione, formed during the nonenzymatic succination of GSH by fumarate was confirmed in fumarate hydratase deficient cells using a product ion scan approach followed by hydrophilic interaction liquid chromatography coupled with MS/MS. GSH and its conjugates, including dicarboxyethyl glutathione and glutathione disulfide, were successfully separated on a zwitterionic stationary phase and detected by MS/MS operated under negative ESI mode. The relative quantitation of the analytes in cell extracts was carried out and a correction model was established to determine correction factors under matrix effects and the response mismatch between the analytes. These factors were calculated and iteratively used to measure all analytes in cell extracts, based on calibration curves constructed in neat solution. The model was a closed‐loop calculation, consisting of two sides with each side of the loop presenting a calculation pathway. Deviation of the correction factors obtained from these pathways manifested the model accuracy. The model was evaluated and there was no significant difference between the two pathways.     

Matrix effects in the determination of β‐receptor agonists in animal‐derived foodstuffs by ultra‐performance liquid chromatography tandem mass spectrometry with immunoaffinity solid‐phase extraction

Matrix effects in determination of three β‐receptor agonists including salbutamol (SAL), clenbuterol, and terbutaline in animal‐derived foodstuffs were studied by ultra‐performance LC‐MS/MS with cleanup of immunoaffinity SPE column (IAC). Some animal tissue samples including pig liver, swine muscle, and fish muscle were hydrolyzed by the mixed enzyme solution or HCl solution, and the cleanup efficiencies with SAL IAC, MCX SPE column, and C₁₈‐SCX tandem columns were examined and compared by using spiked experiments. The results showed that the matrix effects in the determination of SAL and terbutaline can be eliminated with SAL IAC cleanup, and the average recoveries of SAL were 77.4～81.5%, 79.0～80.3%, and 85.0～87.2% in pig liver, swine muscle, and fish muscle, respectively. The decision limit (ccα) and detection capability (ccβ) for SAL in pig liver were 0.02 and 0.05 μg/kg, respectively.     

Inferring LncRNA-disease associations based on graph autoencoder matrix completion

Accumulating studies have indicated that long non-coding RNAs (lncRNAs) play crucial roles in large amount of biological processes. Predicting lncRNA-disease associations can help biologist to understand the molecular mechanism of human disease and benefit for disease diagnosis, treatment and prevention. In this paper, we introduce a computational framework based on graph autoencoder matrix completion (GAMCLDA) to identify lncRNA-disease associations. In our method, the graph convolutional network is utilized to encode local graph structure and features of nodes for learning latent factor vectors of lncRNA and disease. Further, the inner product of lncRNA factor vector and disease factor vector is used as decoder to reconstruct the lncRNA-disease association matrix. In addition, the cost-sensitive neural network is utilized to deal with the imbalance between positive and negative samples. The experimental results show GAMLDA outperforms other state-of-the-art methods in prediction performance which is evaluated by AUC value, AUPR value, PPV and F1-score. Moreover, the case study shows our method is the effectively tool for potential lncRNA-disease prediction.     

频域空间密度矩阵重正化群的研究进展

密度矩阵重正化群(DMRG)作为低维强关联体系中电子结构计算的强有力方法被广泛熟知, 并被迅速地应用于量子化学, 不仅在电子结构计算中发挥重要作用, 同时也在近几年迅速地成为复杂体系量子动力学计算的重要方法. 在DMRG框架中, 衍生出了一系列计算动态响应性质的有效方法, 并得到了广泛应用. 本文简述了DMRG的基本理论, 其矩阵乘积态(MPS)表示有效地扩展了该方法的应用范围. 重点介绍了基于线性响应理论的动态DMRG, 在频率空间求解系统在零温以及有限温度下响应性质的算法, 并介绍其在电子关联问题和电子-声子关联问题中的应用, 最后展望了该领域的未来发展方向.     

Linear algebra approach to geometric graphs

We introduce a new linear algebra approach for studying extremal problems in geometric graphs. We give alternative proofs to well-established facts on geometric graphs, as well as new results about triangulations.     

Least-Squares Solution with the Minimum-Norm for the Matrix Equation A^TXB ＋ B^TX^TA = D and Its Applications

An efficient method based on the projection theorem,the generalized singular value decompositionand the canonical correlation decomposition is presented to find the least-squares solution with the minimum-norm for the matrix equation A~TXB B~TX~TA=D.Analytical solution to the matrix equation is also derived.Furthermore,we apply this result to determine the least-squares symmetric and sub-antisymmetric solution ofthe matrix equation C~TXC=D with minimum-norm.Finally,some numerical results are reported to supportthe theories established in this paper.     

Elimination of interferences in determination of platinum and palladium in environmental samples by inductively coupled plasma mass spectrometry

Various approaches were evaluated in order to eliminate the spectral interferences noted when Pt and Pd has to be determined in environmental dust samples by ICP-MS. The chemical separation of Pt and Pd from the matrix components on ion-exchange resins was applied. The performance of cation-exchange resins (Dowex 50 WX-8, Dowex 50 WX-2, Dowex HCR-S, Varion KS, Cellex-P) for the separation of interfering ions was then examined. It was found that Dowex 50 WX-8 shows best performance. The effects of mass, mesh number of resin and concentration of Cl⁻ ions on matrix separation were also studied. Another approach was to use the anion-exchange sorbent Cellex-T, which allows almost total retention of both analytes followed by their elution with 0.1 mol L⁻¹ thiourea in 1 mol L⁻¹ HCl. This procedure however can be used only for platinum determination by ICP-MS. The accuracy of proposed procedures was confirmed by the analysis of certified material BCR-723, and then it was used for determination Pt and Pd in samples of road dust.     

Response time in a tandem queue with blocking, Markovian arrivals and phase-type services

A novel approach for obtaining the response time in a discrete-time tandem-queue with blocking is presented. The approach constructs a Markov chain based on the age of the leading customer in the first queue. We also provide a stability condition and carry out several numerical examples.     

求模糊关系传递闭包的一种算法

根据模糊关系的传递性的特征,文章提出了利用相应的模糊矩阵求有限论域上模糊关系的传递闭包的一种计算方法,该算法可以加快获得传递闭包的速度。通过实例说明了该算法是简便、实用的。